{"id":"W1588246768","doi":"10.1109/iat.2004.104","title":"Speech and language interfaces for agent systems","year":2004,"lang":"en","type":"article","venue":"IEEE/WIC/ACM International Conference on Intelligent Agent Technology","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Human–computer interaction; Variety (cybernetics); Natural language; Natural language user interface; Intelligent agent; Software agent; Interface (matter); User interface; Software; Multi-agent system; Representation (politics); Natural language understanding; Artificial intelligence; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003762126,0.0003689318,0.0003725483,0.0007573917,0.0001550813,0.0003547799,0.002109482,0.0002887279,0.00006470362],"category_scores_gemma":[0.0002138716,0.0003373542,0.0001085581,0.0002874031,0.000132845,0.0003161929,0.0004011423,0.0002932654,0.0002743106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003782983,"about_ca_system_score_gemma":0.0000932854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002040881,"about_ca_topic_score_gemma":0.00008735355,"domain_scores_codex":[0.9974361,0.00004996379,0.0006813988,0.0008740355,0.0005090309,0.0004494783],"domain_scores_gemma":[0.9981476,0.0001030561,0.000360057,0.0008789191,0.0003858824,0.0001244774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005829306,0.0003306542,0.0003699251,0.00009337017,0.0002302313,0.00007413112,0.001698359,0.0006491541,0.03175036,0.9037064,0.001182356,0.05985676],"study_design_scores_gemma":[0.0047035,0.002659169,0.0009094262,0.001847106,0.00009509677,0.00064618,0.006382819,0.1236164,0.7280182,0.07440481,0.05414718,0.002570108],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3161286,0.0004993169,0.6646004,0.008206637,0.006502368,0.001386481,0.00005347721,0.0006551089,0.001967597],"genre_scores_gemma":[0.9900224,0.0003127953,0.007600517,0.0002311145,0.0001998544,0.0002658075,0.00002423948,0.00002581106,0.001317459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8293016,"threshold_uncertainty_score":0.9999079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06223817179464818,"score_gpt":0.3254400998526454,"score_spread":0.2632019280579972,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}